New technique to estimate the asymmetric trimming mean

A. M H Alkhazaleh, Ahmad Mahir Razali

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

A trimming mean eliminates the extreme observations by removing observations from each end of the ordered sample. In this paper, we adopted the Hogg's and Brys's tail weight measures. In addition, a new algorithm was proposed as a linear estimator based on the quartile; we used a quartile to divide the data into three and four groups. Then two new estimators were proposed. These classes of linear estimators were examined via simulation method over a variety of asymmetric distributions. Sample sizes 50, 100, 150, and 200 were generated using R program. The results of 50 were tabulated, since we have similar results for the other sizes. These results were tabulated for 7 asymmetric distributions with total trimmed proportions 0.10 and 0.20 on both sides, respectively. The results for these estimators were ordered based on their relative efficiency.

Original language English 739154 Journal of Probability and Statistics https://doi.org/10.1155/2010/739154 Published - 2010

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Trimming
Quartile
Asymmetric Distribution
Linear Estimator
Estimate
Estimator
Relative Efficiency
Simulation Methods
Divides
Tail
Sample Size
Extremes
Proportion
Eliminate
Observation

ASJC Scopus subject areas

• Statistics and Probability

Cite this

New technique to estimate the asymmetric trimming mean. / Alkhazaleh, A. M H; Razali, Ahmad Mahir.

In: Journal of Probability and Statistics, 2010.

Research output: Contribution to journalArticle

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